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Transcript
Intro
**** · It's so hard to predict what is worth investing time into anyway in AI because a year ago someone would have been go build all your own agents and you might have done really well with that but then open AI comes out with this and you're why did I waste any of this time? Welcome to the artificial intelligence show the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Ritzer. I'm the founder and CEO of Smarter X and Marketing AI Institute and I'm your host. Each week, I'm joined by my co-host and Smarter X Chief Content Officer, Mike Kaput, as we break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career. Join us as we accelerate AI literacy for all.
**** · Welcome to episode 21 of the Artificial Intelligence Show. I'm your host Paul Ritzer along with my co-host Mike Kaput.
**** · We are recording at an unusual time this week. It is Friday, April 24th, 2 o'clock Eastern time. We normally record on Mondays. Feel I went through this already this week explaining a weird time, which I probably did. That was probably this Monday. So, normally we record on Mondays, but Mike and I are both traveling on Monday the 27th, I guess that would be.
**** · Yes.
**** · And despite our best efforts to coordinate schedules to do this on our usual time, it was not happening. So, here we are on a Friday afternoon. Bear with us because I think both Mike and I have had a week it's just we were just saying before we jumped on I don't know you, man, but I'm just mentally fried now.
**** · 100%.
**** · And it doesn't help that we get new models, agents everywhere. a lot going on. So, we certainly weren't going to skip this week. There's way too much happening to not do it. But, we have a lot to talk about with a new model from OpenAI. new Deep Seek model. everybody's rolling out something to do with agents this week. So, we will do our best as always to cover it and give you the best analysis we can to make it make sense and actionable for you. So, today's episode is brought to us by MCON, the marketing ad conference, now in its seventh year, which Mike is hard to believe. we launched this conference back in 2019, believe it or not. So, this is our seventh year. It's going to be October 13th to the 15th in Cleveland, Ohio. that is our home.
**** · That's why we've always held it in Cleveland. It's an amazing place to run an event, but it is our home base. And that's why, I do get asked sometimes, why is it make in Cleveland?
**** · that's why it's our it's our hometown and we wanted to build something that meant something to our local community and economy. And so, we thought if we could build an event that would draw thousands of people, why not do it, somewhere that mattered to us? So, so that's that's why it's in Cleveland, in case you were ever curious. the conference is bringing together more than 2500 marketers and business leaders focused on one thing, how to make AI work inside your organization. We've already announced two keynotes worth the trip alone just this week. I'm extremely excited about both of these. Karen How, the author of Empire of AI is back. She was our very first keynote in 2019 and she's returning with a deeper story. How ideology, money, and power shaped open AI and why it matters to every business leader now. funny quick backstory, Mike. you'll probably remember this, but when I did the Mecon in 2019 and I was trying to create the agenda for it, I had read an article by Karen at the time. She was working at MIT Tech Review and she'd written an article called what is AI? And it was this super simple, beautiful visualization of what is and is not AI. And I reached out to her at the time. I said, Karen, have you ever done this as a talk? Because I need this talk at Meon. It's a great introduction. and she had not, but she turned it into a talk for us. And so back in 2019 before Karen, blew up and become this best-selling author and you I think she wanted at the Wall Street Journal at the time and just an amazing person, amazing author, amazing researcher. And so she came and did that talk then and then she led a panel for us on ethics on AI and ethics back in the time. And so I've been trying to get her to come back ever since. and the stars aligned this year where she was going to be in the country for a few week period and we were able to get her to agree to come back. So I'm I'm extremely excited about that one.
**** · And then Dan Slagen also returned. Dan was with us in 2024. He was on the main stage. at the time he was the chief marketing officer of tomorrow.io put on an amazing talk. He's now senior vice president of marketing at Zapier. So he's going to be back with a extremely practical grounded view on what's going on. We've talked a little bit recently about some of the things Zappier is doing, especially on their AI literacy and how they're infusing it into their own employees and workforce. So, Dan's going to have a great story to tell. I think we're still trying to figure out which story to tell, cuz there's so many angles he could go with. So, Dan will be back. and new speakers can be added every week. We have a couple other really big keynotes we're working on now. So, stay tuned. But mcon.ai, it's Mic.ai.
**** · And you can use POD 100 to save $100 off current rates. I think the rates go up every 30 days or so. So, get in early, get your tickets early, and you can save hundreds of dollars and then use that pod 100. So, again, it's mcon mic.ai. Mike. AI pulse survey.
**** · So, if you're new to the podcast, every week we go through a we put up a pulse survey and our listeners can go through and answer two quick questions. It takes about 30 seconds. so it's smartrx.ai. AI/Pulse.
**** · We'll tell you this week's pulse questions at the end of the episode today. But on last week's episode on 210, we asked, "Is AIdriven search chat GBTC cloud Google AI mode starting to affect your website's traffic yet?" 43% said don't track it. 26% said not yet, but watching. 23% said some impact. And then major impact or clear decline was a small percentage. Mike, I don't know what that is. less than 10%.
**** · Yeah.
**** · and then the second question was are AI agents genuinely starting to change how your team works or is it still mostly chatbased AI? So by far biggest percentage 53% said still mostly chat. 30% said early experiments only 13% said agents are real for us. and then no AI yet is a very small sliver. Yeah.
**** · that one's going to become more relevant today's conversation. Mike, because today is all about agent.
**** · so let's get it kicked off though because we did have a new major model release from Open AI.
GPT-5.5 Launches
**** · Yes, Paul. So, OpenAI launched GPT 5.5 this past week. They call it a quote new class of intelligence for real work empowering agents built to understand complex, use tools, check its work, and carry more tasks through to completion.
**** · It is OpenAI's first fully retrained base model since GPT4.5 and the first API model from the company to ship with a 1 million token context window. So pricing comes in at $5 per 1 million input tokens, 30 bucks per 1 million output tokens at roughly double GPT 5.4. There's a GPT 5.5 Pro variant at $30 per 1 million input, $180 per 1 million output on a bunch of benchmarks.
**** · GPT 5.5 took the top spot on the artificial analysis intelligence index with it has a score of 60 which is three points ahead of Claude Opus 4.7 and Gemini 3.1 Pro preview. It leads the browse comp benchmark at 90.1% Frontier Math Tier 1 through 3 at 52.4% 4% and it also posted an 84.9% on their GDP valve benchmark which is measuring how AI is good how good it is at doing real work. Sam Alman framed this release as saying hey we believe in iterative deployment although GPT 5.5 is already a smart model we expect rapid improvements. There were a couple people who also reported after having early access some of the results they were getting. So Aaron Leby, we talked about a bunch, CEO of Box said the model saw a 10 percentage point jump in accuracy on their most complex knowledge work evals.
**** · the Lovable team, the vibe coding tool, Lovable, they reported a 23% reduction in tool calls per request. I called it the most capable model for people taking on complex build with technical depth. So Paul, lot of stuff we can unpack here. just curious about your broader thoughts here. here. just again another new model but there was a big emphasis open AAI stated just outright about agentic coding computer use knowledge work and early scientific research they said those were areas where these gains of the model were especially strong and I don't know if you could more succinctly put a series of trends of exactly where AI seems to be going. We've talked a lot recently about OpenAI refocusing. they, cutting the Sora app. they're thinking about robotics, but not heavily invested in it quite yet. They dropped the idea of having a social network. So, they're doing their best to try and refocus. I think in large part due to the success of Claude, if we go back to the start of the year, not only did Claude all of a sudden start getting a lot of headlines and a lot of attention for the quality of its work, not only in coding though, but in knowledge work and we talked about it so much on this show, Mike, of the ways we've been using Claude and it just seems to have been post-trained really well to do knowledge work to do strategy documents and research papers and and so open has been watching anthropic making gains and seeing their revenue skyrocketing and a lot of it's coming from their work with enterprises and I'll share a little bit more about my last couple weeks but I was at the Google next event this week and every person I talked to was using claude they have co-pilot licenses they have Gemini licenses but I didn't talk to anybody that wasn't at least experimenting with claude as well and in some of the cases I was talking to massive fortune50 enterprise leaders in some cases who are in charge of AI within their organizations. and they're giving people clawed access on top of everything else. So, OpenAI is seeing this, they're hearing this, it's why they're they're having to not only do all these deals with the consulting firms, but they have to focus on the real work. And so, when you read the post that they put out about this release, it's it's very obvious, as you said, where they're going. So, it said, "We're releasing GPT 5.5, our smartest and most intuitive to use model yet, and the next step toward a new way of getting work done on a computer. GPT 5.5 understands what you're trying to do faster and can carry more of the work itself. It excels at writing and debugging code, researching online, analyzing data, creating documents and spreadsheets, operating software, and moving across tools until a task is finished. Instead of carefully managing every step, you give GPT 5.5 a messy multi-part task and trust it to plan, use tools, check its work, navigate through ambiguity, and keep going. Now, we're going to talk a lot about agents on this episode, but this is the stuff people have been using codecs and claude code for and things that, and Gemini, but the what they're saying is the average knowledge worker wasn't seeing those same capabilities. You had to be a developer. You had to be a technical person to get those capabilities which is what we've been stressing on the show is that these claude co-work open call these things they're great for developers you have to be technically minded we're trying to talk to the people who are outside of that world who are trying to just go in and build an agent and then they get into an anti-gravity what the hell do I do with this it it's not intuitive so where openai is obviously going here is moving in that direction of bringing those coding capabilities in a more reliable secure way into the platform that the average knowledge worker would use.
**** · So they continued, they said the gains are especially strong in agent coding, computer use, knowledge work, and early scientific research. because the model is better at understanding intent, it can move more naturally through the full loop of knowledge work, finding information, understanding what matters, using tools, checking the output, and turning raw material into something useful. And then just some quick context here, Mike. I listened to this core memory podcast with Ashley Vance, which I think it's a new podcast. and if I'm not mistaken, it was a gated podcast, you couldn't get it.
**** · And then someone had proposed well, why don't you raise money or something and and make it open. And someone paid $100,000 to unlock this podcast. And so just this episode, so it was with Sam Alman and Greg Brockman.
**** · So, Ashley Vance sat down with the two of them and I think it was the first time they've ever done an interview together. So, on my flight back from Vegas on Wednesday, I listened to this and I'll just highlight a couple things because this came out as a prelude to 5.5, but Sam and Greg were obviously talking about some of the things they were doing. So, Sam talked a lot about the tech, but said they haven't connected the dots enough on what the abundant future will look I thought this was fascinating because an episode or two ago I was saying how there was a PR problem in the industry and how they were all talking about this abundance and yet no one understood what that meant. So I was fascinated to hear Sam echo exactly what I was saying and he was we're not doing a good enough job as an industry making it tangible for people what this amazing future is that we're envisioning. he also said they're not far away from a model that knows the complete complex complexity and context of your life.
**** · This is the memory component. And I think this is a really important thing for people to understand. And so when you're using 5.5, you're they're obviously starting to rely more on memory, but they're also relying more on the fact that the memory is just going to get better. And so when you have models 5.5 and eventually six that have full context through memory and they also are able to continually learn which I'll talk a little bit more about in a minute. The need for prompting in the ways we've become adept at prompting goes out the window. you don't need to do context and interview me and all these things that have become standard ways of prompting because it knows everything already. And so prompting just becomes hey do that report for me that I have to do on Sunday nights and it's okay and it goes and does the and then Greg along those lines talked about personal AGI which is the first time I think I've heard him talk about it in this terms. So what they're saying is rather than a universal AGI as this model and then the next generation of models come out it starts to know you so well that it feels general intelligence to you because it does have this full context and memory and ability to learn from what you're doing. And so on in that vein, they talked a lot about this idea of still this jagged intelligence that we still are in this age where sometimes these things feel superhuman and then it gets hung up on a stupid thing and you're "Oh, it's no smarter than a preschooler when it comes to this thing, but it's superhuman at this other stuff." And then they just really talked a ton about agents. So Greg said at the moment they're at the transition agents.
**** · Agents are going to do all the work.
**** · They specifically highlighted context, computer use, and memory as the core components. They want to bring codecs, the coding capabilities of codecs to everyone. And that's what I think we're going to start to see. We'll talk about the agents from specifically for this new workspace agents in a moment. they want personal AI that is not only feels AGI, but it's proactive. It anticipates what your needs are going to be and it does things in the background for you and surfaces things "Hey, you asked for this last week. I went ahead and ran this for you." that stuff. So, the interview's worth listening to. it's nothing groundbreaking I was expecting with the two of them together they were going to talk about a whole bunch of things they'd never talked about, but they did get into the evolution of the relationship, the evolution of Greg's role and what he's doing moving forward.
**** · And then they did talk a little bit about the Elon Musk lawsuit and how painful it was for both of them personally and one because Greg's personal journals got put in as evidence so real personal stuff was out there. but Sam did say at the end that his biggest fear now is that Elon's going to drop the lawsuit the day before it starts because Sam's "We went through the hell for this. I want it all out there now." all of our lives have been put out for everybody. Let's have this trial and let's hear let everybody hear what really happened. So, I could totally see Elon dropping the lawsuit just messed with them enough to make their lives miserable and then screw it. but if this goes to trial, man, it's going to get it's going to get messy and make for some pretty interesting conversations.
**** · Yeah, I bet Greg Brockman is regretting keeping a journal at this point.
**** · Yeah, he glossed over it as it is what it is, but it's no one wants their personal thoughts out there in the world this.
Workspace Agents in ChatGPT
**** · so our next big topic this week, OpenAI has launched workspace agents in chat GPT this past week. So the company calls these an evolution of custom GPTs and positions them as shared agents that can handle complex tasks and longunning workloads across tools and teams. So teams build an agent once essentially and use it together inside chat GPT or Slack at the moment with the agent improving over time. Now agents are being powered here by codecs running in the cloud. So they keep working even when the user is offline. They can run on a schedule or they can be deployed directly into Slack channels to pick up requests as they come in. OpenAI is shipping pre-built templates here for finance, sales, and marketing agents with out of the box connections to things Slack, Google Drive, Microsoft Apps, Salesforce, and more. The availability of these is a research preview now for chat GPT business, enterprise, edu, and teacher plans with a gradual roll out across business and enterprise over the next several weeks. The feature is off by default for enterprise workspaces pending admin enablement and the pricing appears to be brief for the next couple weeks after which they shift to a credit based model but they're still not have not yet disclosed the rates and things here. on the governance side openai is shipping with these role-based admin controls over who can create and share the agents. there's required human approval for sensitive actions sending communications or modifying records and a compliance API that exposes every agent's configuration and runs and safeguards as well against prompt injection attacks. So, Paul, I know this is something you and I have been talking about quite a bit this week. You've done a little initial experimentation with this. any thoughts how big a deal is this? I so this is one of those things where you initially look at you're this might be a really big deal. and I'll I'll give some brief context.
**** · So I was as I mentioned I was at Google Next this week and it was all about agents everything every talk from the leaders of Google about agents. Yeah.
**** · And one of the things they previewed was this agent designer and then I sat in a master class where you could build agents with this agent designer and I was this is slick this is really cool direction. Unfortunately, it's not available. I don't know when it's coming, but sometime later. I think it's in some a re research preview mode. So, almost everything that Google showed was for developers. So, it's vertex AI, anti-gravity, things that. And you need some elements of technical capabilities and you probably need it involved.
**** · So, I was just that this is cool. Oh, wait. I'm disappointed again. And then that same day, OpenAI announces these agents, as does Microsoft announce their agents. So, we'll get to that in a minute. So, I see the ChatGpt one and I'm oh my gosh, that's that's amazing. Is that available? can we get this? So, I go into my ChatgPT account and sure enough, there it is. And I was awesome. And so, you just click on so again, I'm I'm in our team account for Chat GPT. And I just click on agents. that's in the left column and then I can click browse agents and I can do browse templates and you immediately get a sense of what's what's possible now.
**** · it shows there's also recent uses so you can look and see that you can see a built by me agents and the smarter X directory in our case. So if you've ever gone into the custom GPTs area it's that but for agents I would say it's the easiest way to envision how this works. But the beauty here is they have these pre-built templates and I'll just read three of them quickly to you because it gives you a sense of what's going to be possible. So they have a template and you can start with a template or you can create your own by just using words hey I want to keynote abstract writer.
**** · So they have a chief of staff and this is how they describe it. Prepare a high signal operating brief for from schedule inbox and team chat context.
**** · Great for users who want sharper priorities, meeting prep, to-do capture, source link, follow-up guidance, and requested email or chat follow-through in one concise daily artifact. And then you can connect it to Google and Microsoft calendars, Microsoft email and teams and Slack. They have a data analysis one that's again a custom or a template agent, a data analysis plug-in arranged around the life of an analyst u rather than a tool checklist. So use it to sharpen the question, write and improve SQLs, inspect the shape of a data set, be build clear visuals, prototype dashboards, and run a final quality pass. So just teach it skills that are specific to what that person would do. In this case, the agent. And then one other one, sales assistant agent, use generalized sales workflows for account intelligence, competitive research, value engineering, meeting prep, follow-up, pipeline planning, seller coaching. Great for teams who want stronger prep, clearer strategy, and better execution across the deal cycle.
**** · And then it shows you a bunch of bunch of capabilities. And I I'll do one more customer support agent. So this is a generalized customer support workflow for ticket triage, case investigation, response drafting, escalations, customer research, and knowledge creation. So now with each of these, you can connect it to things. So, I just picked these because every one of those, if we connect it to HubSpot, completely changes our workflows and potentially our staffing plans. Yeah.
**** · So, if these things work in a reliable environment that I, as a CEO, am okay with us experimenting with, it completely evolves the way I think about how we're going to do our hiring this year and how we're going to analyze it.
**** · And the thing I keep coming back to is this need for to somewhat centralize, we'll talk a little bit more about this in the next topic too with this agent usage, but this idea of centralizing the building of these things. And so what I did is on the flight back, I messaged Mike and Jeremy on our team and I put a calendar invite for next week and I was we're just going to run a lab on this, a hackathon lab and let's just take an hour together and figure out what these things can do. Yeah. And so Jeremy and our team's looking into the connectors and trying to make sure we're, good from a perspective, a safety perspective to do these things.
**** · And then we'll we'll do this.
**** · we'll spend an hour next Friday hacking together and let's let's pick a couple of these agents, let's build something and see what happens. and it again I don't want to overstate this, but if these things work, this goes back to when we first got some form of workspace studio agents in Google and then it was it's they're they're fine, but they really are just this is a few months back. They're for automating email stuff and some calendar things, but it's okay. They're just rules-based things though.
**** · It's nothing too crazy. This is a different level. this is truly doing the work and the ability to build agents for each role in the company. it really just starts to change how I think about this because it's so easy to do. you could train anybody to do this. Even somebody who's has been hesitant to do anything with AI.
**** · Yeah.
**** · We could run an intro to AI 30 minute class. Here's what it is. Here's how it works. Here's what agents do. And let's build an agent for you in real time and you can just do these things in these lab environments. So I don't know I until we do this next Friday Mike and until we have time to play around I don't want to say this is transformative per se but it has all the signs of being a very important thing and then Microsoft did the same thing Google with this agent designer is going to do the same thing it's pretty clear that by fall of this year if not sooner depending on which platform you're on they're all going to enable a knowledge worker, a non-technical knowledge worker to build agents and run them.
**** · it's really interesting to read through the announcement about these and start playing with them because what really occurred to me is it was a subtly important point to read that it's powered by codecs because if you're if you're one of these more non-technical user, which I am one, if you haven't used codecs or claude code, this is why people are freaking out about those tools because it's a preview essentially and it's a different modality.
**** · And not exactly the same as these agents, but they do the same types of things for non-coding tasks.
**** · They do agentic work using files, code, tools, and memory to do skills to do way more than you can do with a prompt or just a chat. So, I think people are about to wake up to what's possible here. And just to connect the dots, this is why we keep harping on about these tools because the game changes when you go beyond just chat, I think.
**** · Yeah.
**** · And it changes many things and organizational design I said. Y yeah it's again I don't I don't want to oversell it but I said you if you go back to episode 141 and even go back to episode 87 prior to that Mhm.
**** · my projection was that AI agent explosion would happen 2025 2026 would be the starting point of it and then that would continue on and by 2027 we would completely transform work with agents.
**** · So this is something we've been known was coming for multiple years. We've been talking about this and I feel we are we are clearly in the very early stages of not just the agent capabilities for the technical people and for development work but now bringing that to knowledge work to make it as simple as building a GPT which leads me to the usage and stuff because yeah there's so many people who've never built a GPT so even that is advanced for most average users of this technology.
Agent Usage: Separating Fact from Fiction
**** · I want everyone to keep this discussion in mind as we get into this next topic because Paul, we've been you and I have been talking quite a bit informally this week about agents at large and how you deploy them inside a real business today. So, a couple updates that came out and then we're going to get into what this discussion about agents has looked for us personally over the last couple weeks. But first up, some things that spurred this discussion.
**** · So, first we saw Jason Lmin at of Saster, owns and runs Saster, posted a pretty widely shared take this past week about their use of agents in how they run that event and some really interesting stuff on podcasts and on posts online where he's talking about using all these specialized AI agents to essentially run different parts of the company. They use Artisan for outbound, qualified for inbound, agent force for reactivation.
**** · They use agents for new customer acquisition. At the same time, Microsoft also you had mentioned made co-pilots agent capabilities available generally across apps and co-pilot. and also we talked about just how open AAI is rolling out workspace agents.
**** · Google's hyping up agents Google Next, which we'll talk about, but these land in the middle of this bigger conversation you and I have been having about where we're at on all this and the open questions around AI agents because there's no shortage of voices we hear from them out there asking these some version of the question, why aren't you all in on agents? why aren't you doing every possible thing you can with agents now? And Paul, I don't know, correct me if I'm wrong. We're not anti- agent. I feel they're 100% the future and we're actively experimenting with general purpose things agent claude code and codeex. We have not gone all in yet on things open claw but there's all these really important open questions and nuance and I feel people are just shoving under the rug here about what is actual production usage look What about security? What are the specific use cases that matter for a business? and the usage question you just alluded to how do we price the usage of these things? So Paul, let's just get into this where do you want to start here? We talked about that's great.
**** · Yeah.
**** · So really what happened is so I got back late Wednesday night I'd already put this lab meeting on the calendar for Mike and Jeremy and I and I hadn't had a chance to play with the agents yet and so I got in the office Thursday morning and I was let me just jump in chat BT real quick. So, I jump in and I'm browsing these templates and looking at it connections.
**** · I was "Oh my god, this might be it. This might be what we've been waiting for." And then Mike came in the office and I was "Dude, look at this." Showing him these sample agents and these templates. And so, again, coming fresh off of Google Next.
**** · I all of this is fresh in my mind because I met with some really interesting people and it's just that random how sitting next to somebody at lunch randomly or the person you're sitting next to at the keynote and you just you have these conversations and these are you might randomly run into a person who's heading up geni adoption managing token budgets at these major companies.
**** · Yeah.
**** · And she what are you doing what what's happening at this company? What's going on with your developers? What's going on with marketing sales and customer success? how real is this stuff within enterprises? So these are the kinds of conversations I'll allude to often on the podcast we're talking to the real people and there's this balance between developers who are hardcore pushing the frontiers of everything that's possible seeing into the future a future that no enterprise is going to touch for a while. they aren't going to do those things. And so when we're talking about this stuff on the show, we're trying to talk to the practitioners and the business leaders who are the non-technical people often who have to figure out what does this really mean? They're trying to solve for what are the token budgets we're giving our developers and some people are oh let's just do token maxing burn all the tokens you want and then I talk to somebody who's in charge of tokens and they're burning through our whole monthly budget in two days. It's how are we supposed to budget for that? And they're going back to these vendors being we can't do this. This isn't a sustainable way to handle this. Then there's the vendor selection. Do we go all in with anthropic or they're well, is chat GBT 5.5 is that a good model?
**** · Should we be using that or is this new agent designer from Google going to be the thing and should we just put all of our eggs in one basket with Google? So these are tough choices. The pricing models, getting back to the token budget, I've been transparent before about this. I just went into HubSpot today. We're we're already out of credits. I'm how the hell did you run out of credits already? That it's 3 days old is the billing cycle. what did we do to run out of credits?
**** · And I went in and I'm trying to audit. Where did the credits go? what are they being used for?
**** · And it makes no sense. And so, I'm just God, this is so frustrating. And then you mentioned risks. The other thing we'll hear about and the SAS episodes are amazing, by the way.
**** · We'll put the link into it. They're just here's what we're doing. we're using 20 agents for this for that. And you start to realize that when you are on the frontier trying to innovate with these agents within a real business, how the hell do you govern them? okay, now there's 20 agents running loose that have access to all these different connectors and these people have the freedom to just go get more whenever they want and Mike can go get this subscription, Jeremy can that's and so now you have to manage these things and these agents, they function off of knowledge bases. they function off of skills. Those things get outdated. how are you managing those and updating them? Is that in a Google sheet? where are we doing all this stuff? And then at Google Next, I watched a a demo from the co-founder of Whiz, the recent acquisition for for Google Cloud, and he was showing how they're managing the risk of these agents. And it was it was beautiful. it was incredible to watch, but also makes you how makes you aware of how unprepared most people are for everything that goes into running and governing these agents as they get access to more and more data.
**** · so yeah, I don't know. I just keep coming back to I love these practical use cases Saster is doing. It's inspiring stuff. it's really cool to hear these stories and in a real business that's our business. they run events. It's it hit close to home for me and I listen to what they're doing. It's "Oh, that's pretty cool idea." But you also listen to them and they're being totally transparent about the fact that they're just figuring this all out because they'll build something in Replet and then they launch it and then it breaks and they're "What do we do now? how do we fix this? we have no idea what's even happening." and then they're going and talking to Claude and being "What broke? how do you because they're not the people who would usually take those things to production." And that's another element of this agent stuff. It's we're being empowered to build these things, but I don't know how to take things to production and I don't know how to deal with it if something breaks.
**** · So I don't know. Yeah, it's we could go any direction with this. But those are just some of my thoughts for the week, having spent the week seeing agents being debuted, hearing them talked about, and then talking with real leaders at massive enterprises who are the they're nowhere near prepared to do this stuff with agents outside of their developers. And even then, it's it's a free-for-all and they have no idea how to manage the tokens and which vendors to use. And so yeah, I don't know. It's it it is the wild west now, but the people who are figuring it out are getting a really fast advant competitive advantage.
**** · Yeah.
**** · And I wrote down as we were preparing just a few big unanswered questions I have about agents or let's call them at least not sufficiently answered. I'm going to share them really quick just in case helpful to people. But first is really how can I more clearly think about different let's call them types of agents because in a practical sense the more I learn the more there's not just one type of agent really quad code runs agents to do things in real time with periodic guidance partnership handholding from humans but that's materially different in practice from something openclaw which can do similar stuff but does so persistently and autonomously. And I don't necessarily think one is better or worse. It's just that when I think about this, it's already nuance that people aren't addressing where I'm "No, it's not just AI agents." It's these are two at least very distinct paths to me. And I'm sure there's others in here I'm missing. But I think there's more nuance to this. just because I'm not using Open Claw yet or a 247 persistent agent, I don't think necessarily means you're at a disadvantage. It just totally depends on the use case, **** · So I think about that a lot and I'm still trying to work that out on my own. I often also am thinking what are the actual use cases for always on agents openclaw. That sounds really obvious to say I could rattle off 20 different ways you use these. And keep in mind again reference the previous segment. I am not bearish on these. I think this is the future. But there's the real consideration if I have to worry about this thing all the time, if I have to manage it all the time or try to troubleshoot it if it breaks regularly, how is it remotely worth it for me to spend time on this versus something shouldn't I just be building out even better and more expansive skills for quad code or building the workspace agents in chat GPT? I don't know the answer here, but that's a real consideration for me.
**** · And then finally, you just hit on this, how in the hell do you pay for 24/7 persistent agents? I feel there was this honeymoon period because I think until really recently you could just plug openclaw or something into your Clawad Max account, and use it that way. So you didn't have to just pay via API, I don't think. And you can't do that anymore. They turned it off. So, how am earth am I going to spin up a $500 a month agent to do my grocery list? I'm not think that much, but I have no idea. That's the point. It could cost 5 cents. It could cost $5,000 a month. I genuinely have no idea how to gauge this. And that's just a personal experimentation. how in the heck do you figure this out as a business?
**** · how would you that's what you're getting at, Is there's no predictability here. You can't budget for this, But they've already shown in the last 6 months they're going to keep changing the pricing models. So then, and I'm not saying they're going to do this in a deceitful way, but the way this traditionally works in business is you get somebody hooked and then you jack up the price. Yes.
**** · So, let's say for us, we go next week on Friday. We're "Oh my god, these agents are incredible." And then we build a team internally that goes department by department and looks at workflows and problems and goals and rocks and says, "Okay, we're going to centralize the building of agents because it's going to be too complicated. if we have everybody doing their own thing and let's get this small team together. We go through, we prioritize these things, we start tackling a couple workflows, couple problems at a time. You build a bunch of agents, they're crushing it. They're part of our $20 a month per person plan and then all of a sudden they're not.
**** · Now they're HubSpot's model where we're burning credits and I have no idea where the credits are going.
**** · And to your point, maybe it's now 5,000 a month instead of 300 a month, but now I'm hooked. now these things are built into our workflows.
**** · So, and maybe they don't change it in two months, maybe it's in a year when they figure this out. and it goes back to that pricing and I think I I said this to you yesterday morning, Mike. I'm I don't get how this isn't eventually human replacement cost thing. it just seems if there was a simple way for the labs to calculate the value of their own technology, which I don't think they're currently capable of doing, they would just charge more for it. So for example, if I go into these agents next week and I figure out wow, we can build a customer success assistant that's going to do these things each week, each month. And if I had to hire someone to do that, that would be a 100 hours of work.
**** · That's a full-time hire that this agent's going to do that work.
**** · And now let's go do the same thing for sales. we'll build an SDR agent and it's just going to do what an SDR would have done. or an event market or whatever. if we figure out a way to do it, then I I would happily pay. if I knew as the CEO that agent I just built or a collection of agents working together is doing the work of three people and opening act came to me and said hey built these agents the value of that would be 300,000 a year we're going to charge you 3,000 a month instead of 20 bucks a month. I'd be yeah let's go. Okay. And so I feel for finance to truly get involved and manage this process as these agents become more prevalent within organizations, I can't imagine how a token or credit based budget whether you're constantly running into a limit is in all possible or scalable for anybody. And I keep coming back to it has to be simple. It has to be clear.
**** · It has to be understandable. I'm paying X a month. You're I'm getting use of these things. And I don't know if it's just these models get 10x cheaper each year. So maybe it's at some point over time maybe.
**** · Well, yeah. Maybe at some point you're just 5.5 is good enough. these agents crush it. I don't need GPT7 and I know that it's going to cost you the lab 10x less to serve me this model in 12 months. So yeah, just keep let me stay on the old model. I don't know. Or maybe that's where the open source stuff comes in. It's once we have an open source model that's good enough the Deepseek, the numbers on DeepSeek are that it's on par with some of these frontier models, **** · And so does it go back to the open source? Does it swing back where you're "Yeah, I'm I'm happy with fifth generation models. I don't I don't need I don't know." And I don't I truly don't think the labs know because they've focused so much on building for developers that are cool with the token maxing model and we're just going to pay for our tokens because they're used to that approach and I don't think they've yet solved for how to charge the way SAS traditionally would have what is the evolution of a seatbased license. yeah and then yeah then you're HubSpot and you're okay I'm just going to build these agents and I'm just going to connect them over to HubSpot.
**** · So, I I'm going to get rid of a bunch of my seats because I don't I don't need them anymore and I can just access it through ChatGpt.
**** · Yeah. There's a lot more nuance to it than just go use agents.
**** · Yeah.
**** · Yeah. And I think sometimes you get push back on, the not trying to belittle the the capabilities of these agents or not give them enough significance. I just think sometimes people don't have the nuance of what really happens in an enterprise and how complex this is and that's we spend our time talking to these companies all the time who can't even get co-pilot rolled out or nobody's ever been trained how to build even build a GPT or analyze a workflow and figure out where AI can fit into it. It's so messy when you get into the real stories of adoption. It's easy to just see the technology and think oh my god everybody should be doing this and it's no they shouldn't. It's not it's not ready for prime time yet. But if you can embed codecs and claw code into the user interface that the average knowledge worker can use them, it changes everything. Well yeah to your point you mentioned to me in the office is even on the GPT front it's very few enterprises have fully explored what is possible simply with GPTs or simply even with connecting standard chat to valid useful data sources so it's there's so much value to be acred and created there it's I'm not saying you don't need agents and that's for sure where we're going but why does it just have to be that this is also a path where I think it was overlooked because we're all, in the Twitter or X AI buffalo where everyone's "Oh my gosh, I'm running my entire company with agents," which is amazing. I'm sure some people are doing that, but the vast majority of people are not remotely close to that.
**** · Yeah. If you're AI native company and you can do that from the ground up, you can take those risks, go for it.
**** · Yeah, for sure.
**** · That's not the reality for the vast majority of companies. these ones that'll be on AI mergin. They're trying to figure out how to work within legacy systems, legacy talent, legacy governance structures, highly regulated industries, it's not the it's not reality.
**** · Well, yeah. and I won't harp on this, but just one more consideration is it's so hard to predict what is worth investing time into anyway in AI because a year ago, someone would have been go build all your own agents. then you might have done really well with that, but then OpenAI comes out with this and you're why did I waste any of this time? Also, the architecture behind some rag and things that. I don't want to get over my skis on the technical stuff.
**** · some of these methods are totally out of date now. So, I should have spent 6 months figuring this out when I should have really just been probably building FPTs or skills or something and then they flip the switch and I can just click a few buttons and make an agent in Chad GPT. It's a very hard I'm not saying that's the path, but it's really hard to predict should you just wait until it becomes a little easier to do.
**** · **** · Paul. So, before we get into rapid fire, one more announcement for this week. This week's episode is also brought to us by AI Academy by Smarter X, which helps individuals and businesses accelerate their AI literacy and transformation through personalized learning journeys and our AI powered learning platform. We add new educational content weekly so you will always stay up to date with the latest AI trends and technologies. And we wanted to spotlight this week our AI for departments collection which now features six course series and certificates designed to jumpstart AI understanding and adoption across departments. now we've got marketing, sales, customer success, HR, finance, operations. I just wrapped up Paul AI for legal this past week. So, I believe that would be coming out next week. Don't quote me on that, but very soon we'll have that done. these are the ideal launchpad for organizations that want to level up their teams and accelerate AI adoption and impact. I'm going to share a little later in the episode a few quick insights from the AI for HR series, which I taught. Just as a note, individual and business account plans are available now. You can also buy single courses and series for onetime fees. So, go to academy.smarterx.ai to learn more.
Google Cloud Next '26
**** · Okay, Paul, first rapid fire. This past week, you were at Google Cloud Next 26 in Las Vegas. That event wrapped up.
**** · Their headline announcement was Gen Gemini Enterprise Agent Platform. This full enterprise stack for building, scaling, governing, and optimizing AI agents. that effectively absorbs and replaces Vert.Ex AI going forward. This bundles a few things a low code agent studio an upgraded agent development kit, agent runtime, a persistent memory bank and governance tools. It also has access to 200 plus models including Gemini 3.1, Gemma 4 and also outside models in there. I think what's that?
**** · I think you're going to claw.
**** · Yes, you claude as well is in there. and then TechCrunch framed the platform as Google's response to things Amazon's Bedrock Agent Core, Microsoft Foundry. they have a bunch of launch customers using this. they paired the platform with a refreshed Gemini Enterprise app. they made a $750 million commitment to their 120,000 partner network to accelerate Agentic AI deployments. There's also a new agent marketplace. So, Paul, you were at the event. What was your read on what Google announced? it seems I think agent is safe to say probably the word of the year here at this point.
**** · That's for sure. Yeah. So, I'm part of the Google Cloud Leader Circle. So, you get it's an invite only thing and so you get a day with Google's leaders and so that was Tuesday. I got to sit through some pretty amazing talks including the opening talk from Thomas Kerrion, the CEO of Google Cloud. and it was very apparent from the jump that they're they're all everything's agents. So he said the goal is to make Gemini Enterprise the best place to run and manage agents. And then in his opening keynote at Google Next, he said bringing AI to every employee in every workflow was the goal they were focused on. now the thing you always have to differentiate with Google Cloud is again when they're talking to developers and when they're talking to the non-technical users and a lot of the things that they traditionally announce is focus more on that developer audience. A lot of things they've built vertex and anti-gravity. They are not for your average user. You really need technical capabilities to get into them. one of my favorite sessions at the leader circle event was Google AI at Google. So they were had some of their key people who are working on AI transformation AI strategy at Google talking about what they're doing.
**** · So I highlight a couple of those real quick. So Ryan Bach who's the VP of AI transformation talked about these lighthouse workflows. And so he was saying they're trying to focus on moving from just tasks into the actual workflows and they want each business unit focused on two workflows.
**** · So they're all about prioritizing where the impact could be. And I really this concept. It's something we've talked a little bit about ourselves internally. You want to get past the cost savings, focus on growth and innovation, which I obviously love that thinking.
**** · He talked about this analogy of going from fishing where you're throwing lots of lines in the water, trying lots of use cases to farming where you're getting very strategic and deliberate and then one of my favorite things echoed that we say all the time is this idea of reimagining work. So seeing significant changes in how teams work together. that they're starting to field experiments within AIF work labs, which that might have stuck with me when I was thinking about doing this lab. I don't know.
**** · but he also talked about how it's so difficult now to predict change and that the lines between roles are starting to blur. We've talked a lot about that on the podcast, how as the CEO, I all of a sudden have the ability to do people's jobs because I can just go in and yeah, use Claw. It's I'm getting annoyed something's not ready I'll just do it tonight. I'll do it myself. And so they're seeing smaller teams emerging where these blurred roles are allowed to blossom. I guess it's cool that everybody can do each thing. there was also Joshua Spanier who's the VP of AI and marketing strategy at Google. He said there even within Google they were struggling to get everyone internally to use the technology which again is counterintuitive to a lot of people but it's it's not if you've spent time with these labs themselves. It's they're just us. they have marketers and sales people and CS people who doesn't mean just because you work at Google that you're AI forward necessarily. So you're there to do your job.
**** · So you talked a little bit about that and how they started a dedicated AI team that was in charge of the contracts, the data sets, the tools, the systems. And so that team builds out a suite of tools that then is shared with teams to use.
**** · So it goes back to that idea of chat GPT agents maybe we just build agents and we say hey sales team here's your three agents and here's CS team and that's a big question for me moving forward and I think for all of our listeners that we have to think about is are we centralizing the building of AI capabilities and then distributing them to teams or are we allowing everybody to just do their own thing. They he just said they relied less on individuals to figure things out. but they made a big investment in ad creative development and testing and they're seeing a massive impact on cost and performance. And then he said something I thought was really interesting. No one joins Google and I wrote any or any company myself to just be efficient no one's goal in their job is to be as efficient as possible, **** · So that's why they focus on trying to bring the creativity and innovation. And then the one other note I'll share, I was really excited about this one. So Jeff Dean was the closing talk at the leader circle the first day. And if you don't know Jeff Dean, we've talked about him on the show many times. He was the 30th employee at Google. He's the one who named Gemini. And the name came from the merging of Google Brain Team and Deep Mind. So it's the sisters the Gemini. and he said that even then, so again going back to this, how mature are agents? He said his words starting to see glimpses of the agent economy meaning we are still early. He highlighted specifically the lack of reliability and trust agents that we should all have in agents now for giving them access to credit card information, filing systems, all of these things. So again, we say this on the show, but this is Jeff Dean, an authority on the topic, saying agents are early. You have to be very cautious with them. You have to be conscious of what you're giving them access to. but they're getting really good and we're seeing glimpses of them making an impact. And then on breakthroughs for AGI, how close are we? Again, there's very few people in the world more qualified to talk intelligently about this topic. He said he thinks we're still one to two major away, which echoes what Demisab says.
**** · And when talking about what does he think that key is, he alluded to that he thought continual learning was likely one of them. Now, having listened to Jeff and others for the last 15 years I've been studying AI, usually if they pick something, it means that it's something they've been working on and they've made advancements on. And continue learning to me I've said this many times in the last 12 months. I think that is the unlock that they that most of these labs think if they can solve for continue learning that the model doesn't stop once it's comes out of its training that it learns humans do from experience and inputs and outputs. It constantly changes its own weights and gets smarter and more capable. That is that might be the final unlock. And my guess is DeepMind has made progress on this and I would imagine the other labs have as well. It's also a very complex thing to put into the world because it can lead to the fast takeoff concept that we're probably not prepared for. So really cool stuff. They do an amazing job at those events. Google's just incredible. and Google Cloud puts on the leader circle is great. And then the event itself I was only able to stay for the first half of the first day of the actual next conference. but even that was awesome. And then finally I did so Sarah Kennedy who's a good friend of mine she led a panel with Shawn White and Bryson Day Shambo. Shawn White the Olympian and Bryson the golfer.
**** · It was awesome. hearing those two guys talk about what they're doing with AI and their sports. But just seeing them and their personalities was really cool. Bryson's a one of those people a lot of people to not Bryson.
**** · I when you sit there and listen I don't know how you couldn't the guy. it was it was a really cool story and I was I was excited to get to experience that.
**** · That's awesome.
Meta's AI Employee Surveillance + Layoffs
**** · Next up in less positive news, a leaked internal memo this past week revealed that Meta is trying to install tracking software on their US employees computers to capture mouse movements, clicks, keystrokes, occasional screenshots across a designate designated list of work apps and sites. And the memo frames the roll out as a way to teach AI models to use computers by giving them real examples of how people use them. And CTO Andrew Bosworth described the end state as one where our agents primarily do the work and our role is to direct review and help them improve. The memo assures staff the tool will not read or read files or attachments, will not be used for performance evaluation, and will not learn incidental personal information picked up from the screen.
**** · There are reports that Meta staff are protesting the roll out internally. I wonder why. separately, Meta also it leaked and then Meta had to announce it, I believe, that it is going to cut roughly about 10% of its workforce with layoffs beginning May 20th. There are additional cuts expected in the second half of 2026.
**** · A big part of this is the cuts are part of their effort to run the company more efficiently and the chief people officer Janelle Gail told people that it was to allow us to offset the other investments we're making. I would just to without oversp speculating point to what other investments Meta is making.
**** · There's exactly one that is quite large and that is its capex guidance of 115 billion to 135 billion that is spending on AI infrastructure that is nearly double what it spent in 20.5.
**** · So AI somewhat adjacently is probably responsible for some of this. so Paul, the reason we're talking about this, be curious about your thoughts first on are they just trying to train agents to do what the humans are doing and then get rid of the humans? Also, what do you think of the cuts and the layoffs due to the capex and investments they have to make to stay current?
**** · Cuts and layoffs expected. I would expect more, not just them. That's obvious. And that's going to continue. the the monitoring of employees. I'll not confident but so I this isn't new. I'll I'll say that.
**** · Yeah.
**** · so there's another social media company.
**** · I did a talk two years ago and after I explained computer vision and the ability for things to be recorded and then analyzed and used in training data, I had an employee from that, it was a different social network company come up and be "Is that why they've been recording everything I've been doing on my computer?"
**** · So, and then she explained to me how they were using the data. she thought, but she wasn't aware that this was even possible. So, this isn't new. it's not surprising at all.
**** · I think that at some point, you have to think about the organizations you want to run and the talent you want to recruit and retain. And at some point, the best talent is going to have choices to make about where they go to work. And if you if you're cool going to work for a company that is tracking everything you do and likely using it to train your replacement. is that is that motivating? it goes back to that thing I just said about Google and saying hey listen we're not nobody comes to Google to work to be efficient. it's not nobody wants to go work to watch an agent do their job. I'm picturing an assembly line and I'm just sitting here just eight hours a day I'm just watching it click around and do things and that doesn't sound a fun career. So I don't know I get what they're doing. I understand this is it's meta. they're going to be on the edge of this and they're going to do things that a lot of people are going to hate and they're going to get bad PR about it and have pissed off employees and that's the story of their history.
**** · they've always done things that were people felt were beyond the line of acceptability and they seem comfortable with that and it's just part of who they are. but I think every other company is going to have to make these same choices because what they're doing is possible. if you want to do a consulting firm or an agency or you want to pick operations or HR or finance in your own company, this tech exists you can train them up and you can build agents based on what people do.
**** · There's a startup last year, I forget the name of it. This is what they did. this is they sold this technology to enable you to do this.
**** · Yeah.
**** · So yeah, if this is new to you, sorry.
**** · this has been going on for a couple years and it's going to get tons of funding from VCs to do this. It's going to get ton of tons of payments to consulting companies to implement this and they will absolutely use it to reduce their workforces. there's no other reason to do it. So yeah, and I'm not even trying to be hard on meta here, this, it's just the reality.
**** · and that's so much of the time when we're doing things this or having these more hard conversations about the reality, we're just trying to share with people what the reality is. And if you're working for a company that's doing this, there is no other reason. Either it's either performance or to train on what you do for your job, **** · I can't think of a third thing that you would do for that. Why? why else you would do it. yeah. So, I think it's just it's just a I guess an awareness thing and you got to know the company you're working for and what their intentions are with AI and ideally you want to understand the responsibly AI principles and whether or not they're human- centered company. it's why I think it's important just for people to have levels of awareness and then educate other people about these things because our, listeners to our show are more likely to get this stuff that they already knew some of this. Yeah. but all your peers, your family, your friends, they don't know this stuff. And so sometimes it's just us trying to do our part to share it so that other people can go and educate people about it.
**** · Yeah.
**** · And to be clear, the intention behind this segment is not to pile on meta specifically because it's not anything new that companies monitor what their employees do on their work machines often. That has happened well before AI. I think what is just really fascinating to me is oh this isn't just for security purposes anymore they're just coming out and saying there's another to your point there's one of two reasons either employees following guidelines are performing i.e.
**** · Are you doing work on your computer? Are you doing anything wrong on your computer? Which has existed for a decade now, major enterprises. But there's this new lane where it's oh, okay, this is training data for exactly for computer use agents. That gets really murky really quick.
**** · And if I'm not mistaken there, I don't think we covered this, but I'm pretty sure two or three weeks ago, Elon Musk changed the terms of employees at XAI and they had to agree to have everything Oh, really?
**** · Yeah.
**** · So yeah, this is for this purpose it's all about training data for gro and that's the thing is they're not even necessarily using this just for their own purposes. They're using this to train their models so the work they do. So imagine if you can collect every interaction that your marketing team, your sales team, your CS team, whatever and you also happen to be a company that trains AI models. you don't have to go license that data because what's happening in other instances is the training labs a scaling AI are paying lawyers and consultants to sit there and have their stuff done so not for a company they work for but saying hey we'll pay you $500 an hour to track everything you do on your computer for a few days and then they're taking that to then train the models to do that the job of those people so yes that is the new thing to your point Mike it's performance tracking and monitoring usage on That's not new. Using it as training data and data to then replace those people is new.
**** · Yeah.
**** · And I didn't even connect the dots until you just said it. this has to have Alexander Wang's fingerprints all over it. This is exactly what they were doing at Scalia. You're **** · Yeah.
Apple Leadership Transition
**** · Okay. Well, our next topic this week, we well, I guess it was technically this week because we recorded on Monday. We covered Apple CEO transition. at the end of the last episode cuz that had broken before we started recording.
**** · that John Turnis was going to succeed Tim Cook on September 1st of this year. in the days since a bit more has come out, especially on that AI angle of what Apple's doing with AI. So Cook and Turnis had an all hands at the Steve Jobs Theater. Cook interestingly addressed some health rumors head on. He told employees, "Hey, I'm healthy.
**** · Energy is high. Plan to be in the role for a long time." Turnis teased an incredible road map ahead. He said AI is going to create almost unlimited potential for the company. According to Bloomberg, Turnis has already overhauled the hardware engineering organization around what he calls a new AI platform designed to speed up product development and improve device quality. on the same day as the CEO announcement, Apple promoted John Johnny Shrui Shrewji to a newly created chief hardware officer role combining hardware engineering and hardware technologies into one organization. CNBC read this reshuffle as a sprint to build in-house chips for devices with Apple doubling down on silicon for ondevice AI. Obviously, we've talked about a bunch. Apple's new and improved AI powered Siri, which has been delayed a couple times, is now expected to debut at WWDC in June of this year. they have a multi-year deal now with Google, reportedly worth around a billion a year to power the new Siri on Gemini. so CNBC is framing this transition as Turnis facing this defining challenge which is obviously Apple does more than just AI but his job is fix the company's AI strategy it sounds and Paul obviously it's so early here but given the new details what is the your initial read on do you think he is the guy for the job to fix Apple's AI problems where do you see this going yeah time will tell but everything I've heard about him from falling online is just extremely positive. Sounds everybody's known he was going to be the guy. He everybody's saying he's the guy. I watched a crazy clip where he was doing an interview about the cinema the cinema display the thing, his first major project there and he was talking about when he was at the I think it was at the manufacturer, whatever. They were piecing it together and they had designed the screws in the back of the display that no one ever is going to see to have 21 grooves in them. It was a very specific number and he took the screw out, took a magnifying glass and found that they had 30 grooves instead of 21 and made him redo it. it just they were trying to stress how what a perfectionist a Steve Jobs type product guy he is. So it seems that's what they're getting. And I said probably in the last episode, I think if they weren't comfortable with the road map they have to execute, it wouldn't be the time. So they're obviously very comfortable here.
**** · Interestingly, at Google Next, Thomas Kieran, when he was doing his opening keynote on the actual first day of the conference, he did mention Apple.
**** · They just put the Apple logo up and everybody's cheering and then he just said about them being a preferred provider for their models and that was it. there's no big thing. He didn't go into a ton of detail. He talked a little bit about Siri, but it was that partnership that we've talked about previously on the show. So, I don't know. again, as a longtime Apple user fan, I'm excited.
**** · It seems Wall Street's liked it so far. I don't I think their stock's been doing pretty well since the transition, which isn't always a given when you have a CEO change.
**** · **** · So, yeah. I don't know. Everything seems positive and I hope I've said many times I just I'd love a working Siri. I'd love Apple intelligence to really be intelligent.
**** · I think it, it's billions of users that would get to experience AI in an entirely new way. And I think a very positive and exciting way if Apple solves how to do it the way on the iPhones and all their devices, AirPods and watches and glasses and everything else they've got.
**** · Yeah, I was going to say a very longer term, but people, we included have talked about Apple's fall from grace and AI, but they're also half a chance away from cracking the code on AI wearables. They're the best people to do it. And if they do that, it's game over. it's a whole different ball game, Dude, the data they have is insane. I don't there's so many things Apple does where you don't because they don't feature it. You have to find these things. And I was I was analyzing steps the other day. I love the health app in Apple. It's incredible.
**** · And I track everything. I've shared my personal story about my heart and how it found something with that. but they track things distance between steps just and it's how it's all it's either in my watch or my phone that they're getting the data from. And the fact that it has this data and you just realize the depth of data they can capture from these wearables or from the, the phone in your pocket, whatever it may be. And then you start to imagine my goodness, what could they do with that data?
**** · Yeah.
**** · if they have the intelligence baked in. So if you're I'm serious if you've never done it before, go into the health app and just click show all data and just look at the metrics they have on you. It's wild.
**** · And then an experiment I did which worked somewhat well is then have Claude code go build some things to connect to that data and then tell you some stuff about it which is interesting.
**** · Fascinating.
**** · it's a lot of trial and error involved. Not perfect. you probably just get the same thing Apple Watch. But it was a fascinating experiment.
**** · Apple watches and if you've never had I was a watch guy before I collected watches Nath watches.
**** · I stopped because I the utility of wearing an Apple watch every day. I hate when I would not have the data for a couple hours. you put a nice watch on or whatever to go do a keynote or something and it's a damn I don't have my heart rate while I was talking. And sometimes you want to see that. It's does my heart rate go up when I'm on stage? I'd be curious. So yeah, I just I love that.
**** · So good.
AI Use Case Spotlight
**** · so next up we have our, now regular segment we're doing on our AI use case spotlights here at Smarter X, where every week we're trying to give you a quick look under the hood at some real uses for AI that we're exploring, building, or deploying in our own work and sometimes in our own personal lives. So Paul, I just have a really quick use case to share this week. If you have anything to share, we can talk through that, too. yeah, go for it. So, for me, I stole this one. The use case is not mine, but I don't think the personal mind may steal it because it's from Taylor, our director of research, who's taking the lead this year on Smarter X's state of AI for business report. So, typically we have done for 5 years in a row a state of marketing AI report through marketing AI institute and smarter X where we've surveyed hundreds and then thousands of marketers and business leaders on AI adoption and usage. This year we decided to really expand that out to all functions of a business. So we've got we just closed the survey. We have almost I think over 2100 responses, the most we've ever had spanning every function, industry and company size. So we are kneedeep in creating the actual report.
**** · And it's really interesting because Taylor is taking the lead on this year. I'm overseeing some stuff and reviewing it. But I think I had shared last year or maybe early yeah last year that the report alone used to take hundreds of hours to do all the manual data analysis writing understanding synthesis that years and years ago in 2024 and 2025 I cut that down to probably a few dozen hours which felt an incredible win.
**** · Taylor did the report in a day this year and I've looked at it a cursory fashion and it's really good and we're obviously going through with a fine tooth comb with human oversight for this and there's human complexity and tone and write rew writing and rewriting and reworking but she was able to cut this down another order of magnitude in how long it took. And the cool thing is it wasn't just about time this year cuz in past years I've been oh my god thankfully it didn't take me this long. I got to run to the next thing.
**** · This year me and Taylor have spent a huge amount of awesome time spent going really deep on two things. One, how can we ask even smarter questions of the data and go further and deeper on this stuff to create an even better report. So we're not say we're reallocating the time. We're not netting out with less time here, but it's going to be 10 times better. But also, as part of building out our research function at Smarter X, how can we blow the doors off activating this report both internally for sales, customer success, everyone else, academy, and externally across a ton of different channels, which is an area we've historically struggled with because it takes so long to do all this stuff. So really, it is night and day. Even I was blown away last year by what the models could do, especially Gemini and Claude with both data analysis and writing. This year, it doesn't even come close. They just smoked what we were able to do last year and it's just jaw-dropping. I'm just continually reminded I know this. I see this every day. But then something this is just so cool to see how good this stuff has gotten. And it's really cool because recurring use cases compound. We've done this every year now that we've been able to for several years using AI for parts of this. it just gets more and more every year and the results just compound and compound and compound and it's it's incredible to see. So super excited about that. We're releasing this in a few weeks here so we'll have more on that and more announcements around that. But we're really excited as I can't wait to see it for one and two as someone who has personally spent hundreds of hours in pivot tables building that report I love to hear the stories of how we are solving for making it more efficient.
**** · Oh, and I will I will just note too at our AI for writer summit that is coming up in a couple weeks if you go May 7th. So if you go to marketing aiinstitute.com go to events you can see there's a free registration option. Taylor is giving a talk about exactly how she did this super tactical you can learn step by step how you can do this for yourself too. So go check that out.
**** · That's awesome. Yeah I'll just do a quick one. This is I I forgot I ran this. It's funny. so sometimes I'll just go into JGBT and see what are the recent prompts I gave. So apparently, I said, I forgot I did it. I think this was last night or this morning. I had seen a Jason Kanis maybe tweeted about how we were going to have all these new companies created and that was going to create all these jobs and but not everybody's really made out to be an entrepreneur. And so just that spur of the moment I'm I'm not tired of this argument. I'm an advocate of this idea that entrepreneurship is maybe the thing that balances out the job loss. But I found myself wondering are we seeing any signs of that yet? are we seeing an increase in startups? so I just went into deep research in JBT and I gave it the prompt. I said, "One of the theories about how the economy will account for job losses driven by AI is that we will see a rapid increase in entrepreneurship and the number of startups created. Is there any data showing an increase in startup creation of the last 12 to 18 months?" So, I haven't gone through and read this whole thing yet, but it went through 33 citations and 341 searches and took 23 minutes to write me a report on startup creation, AI displacement, and entrepreneurship since late 2024. and it has a bunch of charts and methodology and sources. And so I guess I'll just use that as a reminder of hey sometimes that's a great use for AI is curiosity. It's I wonder and it can be at the most random moment and you can just set deep research is an agent it's going and doing its own thing. It's taking actions to it builds a plan and then it goes and take actions as a form of an agent and it just goes to work and it does it for 23 minutes and then I forget I did it until I come back into here. but yeah, sometimes those are the best use cases is just that spur-of the- moment. Hey, I wonder if I could do this thing or if I could come up with this idea or if I could create this visualization and then just throw it in there and see what happens. So, yeah, that would be it' be a fun one for me for the week. Now, I got to go read this.
**** · That's the key.
AI Academy Spotlight
**** · So, one other recurring segment we've started doing is each week we spotlight one of the courses in AI Academy to give people real actionable takeaways from the course whether or not you ever end up becoming an academy member just to give you some of the value for free that we're creating in AI Academy. So, Paul, I'm going to go through this week our AI for HR course series very briefly and share some takeaways there.
**** · Sounds good. So what's really cool and interesting and also a little scary in AI for HR is that it is really at the front lines of how AI is changing traditional systems. So and in our research and in creating this course I'm the one who taught this we found that it's AI is creating chaos across the core work of HR. not only is it creating huge opportunities for HR as a function, but they're running into real issues where candidates and employees are using AI, too. And it's not necessarily bad to use AI in your job search, but it leads to all sorts of really messy questions because we're seeing hiring signals get really compromised because candidates are using AI to not only game the system but also just really hack their way through the process and it's you can't use these traditional signals anymore to see if someone knows what they're talking about. So, employees themselves, even after hired, are using AI to do their work in ways managers can't see. This is affecting everything from resumes to performance reviews to just overall productivity. And HR professionals have a really tough job now. And that's the big macro trend. And the one of the practical takeaways that we teach in this course is for your average HR person, this can feel deeply overwhelming. there's so much going on in AI. There's so much to learn.
**** · They're already dealing with the fallout in a negative way sometimes with how the hiring process has changed. One way that we teach and walk you through in this course is just a really simple framework to get started thinking about, okay, I know CHPT does this. I've heard about Claude over here. how do I wrap my head around the opportunities for me in my job? And we use this framework called just pretty simply the three A's. And the three A's are this sequential order to think about AI automation, augmentation, and acceleration. So, first you want to start looking at things where can AI handle low-level, lowhanging fruit, repeatable work that you can have it do for you in order to save time because that's where 99% of knowledge workers and HR professionals especially are really stuck is they are drowning in reactive admin work that is not the best and highest use of their time. So automation is a key initial step and back to that discussion productivity is not everything but freeing up some time so we can be more innovative can be really helpful. And then second is augmentation. So looking at and we walk you through a series of questions on how to surface these opportunities. augmentation is using AI as a co-pilot. So let's say you freed up time by automating some things with AI.
**** · you then can start doing more of the work you're meant to do more strategic more highv value stuff well AI can augment you there to supercharge and just accelerate the value you create there which benefits you and helps you do better work not just faster work and then finally over time after you are effectively automating and augmenting your function as the case may be acceleration is the bigger picture stuff the AI agents the more transformative projects that's where we and walk you through thinking about not just what AI can do for you or how AI can make you better, but what AI can enable that just was not possible before. So, we're talking, we go through a bunch of use cases and examples of that in the course. One really interesting one is is I believe Shopify uses an internal talent marketplace completely driven by AI to match people internally to different roles. That's a really structural long-term almost sci-fi use of this technology that completely upends how the company works.
**** · So that's the practical starting point is running your work and asking yourself a series of questions through those three lenses to sequentially step by step without biting off more than you can chew see some real value from AI out of the gate.
**** · It's a lot of stuff we need to be applying to our HR smart.
**** · Exactly.
**** · Yeah. I have to admit some of the stories even in this course and the case studies and even just some of the research even stuff that didn't make it in you're just I would not want to have to figure this out that Yeah. recently are, there's a lot of that overwhelm feeling.
**** · Yeah.
**** · Of trying to not only figure it out for yourself internally, how are we going to use it, but how do we manage and recruit and hire people who are obviously using it in the process?
**** · Oh, yes.
**** · Yeah. It's a very dynamic space now.
AI Product and Funding Updates
**** · Paul, last but not least, we've got a bunch of AI product and funding updates. So, I've got the a bunch of these teed up last week. There are a lot of things going on. I'm going to run through these real quick and if there's anything that jumps out, you let me.
**** · Go for it.
**** · So, first up, OpenAI launched Chat GPT Images 2.0. Its first image model with native thinking capabilities. It can search the web, generate up to eight consistent images from one prompt, and produce, this is important, produce readable text that is accurate at 2K resolution. It is widely seen now as the number one image model out there and is making a lot of waves.
**** · OpenAI also launched chat GPT for Excel and Google Sheets. This is a sidebar app that lets plus, pro, business, and enterprise users build, edit, and analyze spreadsheets in natural language and pull in connected Chat GPT apps alongside their data. OpenAI also announced Codeex Labs Plus partnerships with Accenture, PWC, Infosys, and other global system integrators to deploy codecs across large engineering organizations.
**** · Anthropic and Amazon expanded their partnership with up to five gawatts of new AWS compute for Claude, a fresh $5 billion investment from Amazon. There may be up to 20 billion more following on that. And a 100 billion 10-year commitment from Anthropic to AWS, plus direct availability of the Quad platform inside AWS. Anthropic also added a memory feature to Claude managed agents, which is now in public beta, that lets agents retain and build on learnings across sessions via file-based storage.
**** · And Anthropic is apparently running a live pricing test on a roughly 2% of new signups with existing Pro and Max subscribers unaffected as the company experiments with how Claude code access is packaged across tiers. So also figuring out that pricing problem we were talking about, Google rolled out an upgraded version of its deep research agent built on Gemini 3.1 Pro, adding a new max tier for extended asynchronous reasoning, MCP connections to proprietary data sources and native inreport charts and graph infographics.
**** · Google also signed a new multi-billion dollar cloud deal with Miro Marotti's thinking machines lab giving the startup access to Google cloud infrastructure and Microsoft as we talked about has made copilot's agentic capabilities generally available in word excel and powerpoint so this just a little more detail here and on the product side this allows copilot to take multi-step app native actions directly inside documents spreadsheets and decks for Microsoft 365 copilot premium personal and family subscribers.
**** · At Adobe Summit 2026, Adobe rebranded Experience Cloud as CX Enterprise and introduced CX Enterprise Coworker and yet another trend of agents, an agentic AI layer that orchestrates customer experience workflows across Adobe's stack. SpaceX struck a deal giving it the to acquire AI coding startup Cursor for $60 billion later this year or pay 10 billion if it walks away from the acquisition while the two companies collaborate on model training using XAI's Colossus Supercomputer.
**** · That's a wild one.
**** · That is a wild one.
**** · I can't I'm not going to get into it because we're running on time here, but that one might be worth unpacking. There's there's a lot to that story.
**** · Yeah. another time.
**** · 10 cent and Alibaba are in talks to invest in Chinese AI lab seats first ever funding round at a valuation now of more than $20 billion with 10 cent reportedly pushing to take as much as a 20% stake. Moonshot AI, which we've talked about in the past, released Kim K2.6, six, a new open source coding model that claims state-of-the-art scores on certain benchmarks and can run 4,000 plus tool calls across 12 point 12 plus hours of continuous execution. And finally, Zapier launched the Zapier benchmarks, a new AI evaluation suite anchored by Automation Bench that tests agents on end-to-end business workflows across sales, marketing, operations, support, finance, and HR using deterministic scoring grounded in two billion plus monthly tasks from 3.7 million Zapier customers.
**** · Maybe we'll have Dan Slen talk about that make maybe. That would be awesome. I would love to pick his brain about that.
**** · I know that's Dan's domain, but Zapier's got a lot going on now. We were talking about their with their internal literacy stuff not a week or two ago, **** · Yep.
**** · So, Paul, that is it for this week. One quick final announcement here. we said at the top of the episode, this week's poll survey will be live when you listen to this at smarterx.ai/pulse.
**** · We're going fullon agent to this week just the topic. So, we're going to ask about things about where is your organization at when it comes to deploying AI agents today and also what is holding your organization back from deploying AI agents more than you are already today. So, I'll be very interested to see that Paul based on the answers from this week as well. But, thank you for breaking everything down for us. Another busy week. I know we've done two episodes this week, so I feel I' I've got a pretty good pulse on what's going on in AI.
**** · Yeah. Yeah. And I was home for two days in a row for the first time.
**** · **** · Well, yeah. And so, yeah, next time we're together, we will be back in town. So, enjoy your travels. Good luck at the experience inbound and I'll be off to I think at the time this drops, I'll be doing the Aqua Engage event and then we'll be back. We'll be back in Cleveland. I'll see you for our Chad GPT agents lab next week that we'll report on the next episode.
**** · Yeah, I'm I'm super anxious. I hope it's everything I think it could be.
**** · I'm very excited.
**** · everyone. Have a great week.
**** · Thanks for listening to the Artificial Intelligence Show. Visit smarterx.ai to continue on your AI learning journey and join more than 100,000 professionals and business leaders who have subscribed to our weekly newsletters, downloaded AI blueprints, attended virtual and in-person events, taken online AI courses, and earned professional certificates from our AI academy. and engaged in the Smarter X Slack community. Until next time, stay curious and explore AI.